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Prediction Intervals

A prediction interval is an estimate of an interval in which a future observation will fall, with a certain probability, given what has already been observed. Prediction intervals are often used in regression analysis.

Papers

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Showing 51–100 of 309 papers

TitleStatusHype
Bellman Conformal Inference: Calibrating Prediction Intervals For Time SeriesCode1
Improving Conditional Coverage via Orthogonal Quantile RegressionCode1
A Temporal Fusion Transformer for Long-term Explainable Prediction of Emergency Department Overcrowding—0
Quantile Regression using Random Forest Proximities—0
Efficiency of conformalized ridge regression—0
Confidence-Nets: A Step Towards better Prediction Intervals for regression Neural Networks on small datasets—0
A Deep Generative Model Imitating Predictive Coding in Human Brain—0
Confidence intervals for class prevalences under prior probability shift—0
A Distribution Adaptive Framework for Prediction Interval Estimation Using Nominal Variables—0
Confidence Calibration for Systems with Cascaded Predictive Modules—0
Assessment of Prediction Intervals Using Uncertainty Characteristics Curves—0
Conformal forecasting for surgical instrument trajectory—0
Efficient Normalized Conformal Prediction and Uncertainty Quantification for Anti-Cancer Drug Sensitivity Prediction with Deep Regression Forests—0
ConfEviSurrogate: A Conformalized Evidential Surrogate Model for Uncertainty Quantification—0
Approximation to Object Conditional Validity with Inductive Conformal Predictors—0
Conditional Testing based on Localized Conformal p-values—0
Conditional Coverage Estimation for High-quality Prediction Intervals—0
Tolerance and Prediction Intervals for Non-normal Models—0
A Data Envelopment Analysis Approach for Assessing Fairness in Resource Allocation: Application to Kidney Exchange Programs—0
Computation of Ultra-Short-Term Prediction Intervals of the Power Prosumption in Active Distribution Networks—0
Combining Prediction Intervals on Multi-Source Non-Disclosed Regression Datasets—0
Approaches for Uncertainty Quantification of AI-predicted Material Properties: A Comparison—0
CD-split and HPD-split: efficient conformal regions in high dimensions—0
Conformal Prediction with Temporal Quantile Adjustments—0
Applying Regression Conformal Prediction with Nearest Neighbors to time series data—0
Adaptability of Computer Vision at the Tactical Edge: Addressing Environmental Uncertainty—0
DST-TransitNet: A Dynamic Spatio-Temporal Deep Learning Model for Scalable and Efficient Network-Wide Prediction of Station-Level Transit Ridership—0
Enhancing Conformal Prediction Using E-Test Statistics—0
Conformal Prediction with Cellwise Outliers: A Detect-then-Impute Approach—0
A Novel Smoothed Loss and Penalty Function for Noncrossing Composite Quantile Estimation via Deep Neural Networks—0
Disease Momentum: Estimating the Reproduction Number in the Presence of Superspreading—0
Uncertainty-aware multi-fidelity surrogate modeling with noisy data—0
Conformal Prediction Intervals for Neural Networks Using Cross Validation—0
Calibrated Reliable Regression using Maximum Mean Discrepancy—0
Discriminative Learning of Prediction Intervals—0
Conformal Prediction Intervals for Markov Decision Process Trajectories—0
Density-Calibrated Conformal Quantile Regression—0
Conformal Prediction Interval Estimations with an Application to Day-Ahead and Intraday Power Markets—0
An LSTM-Based Predictive Monitoring Method for Data with Time-varying Variability—0
Conformal Prediction in Learning Under Privileged Information Paradigm with Applications in Drug Discovery—0
Conformal Predictions for Longitudinal Data—0
CAP: A General Algorithm for Online Selective Conformal Prediction with FCR Control—0
Development and Evaluation of Conformal Prediction Methods for QSAR—0
Conformal Prediction for Manifold-based Source Localization with Gaussian Processes—0
Adaptive, Distribution-Free Prediction Intervals for Deep Networks—0
Conformal Prediction with Upper and Lower Bound Models—0
Accurate and Reliable Forecasting using Stochastic Differential Equations—0
Conformal Predictive Portfolio Selection—0
Conformal Regression in Calorie Prediction for Team Jumbo-Visma—0
Denoising ESG: quantifying data uncertainty from missing data with Machine Learning and prediction intervals—0
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